Advanced Data Science Professional (ADSP)


Have a question about the course?
Chat with an Education Officer or Email:

Select Your Preferred Batch Below:


  • Duration: 4 Day (Onsite) / 24 Hours (Online via Zoom)
  • Certification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination
  • Who Should Attend: Professionals or Anyone interested in pursuing a career as a data scientist and use data to understand the world, uncover insights, and make better decisions

Course Objective

Acquire advanced knowledge on how to use Data Science with Python Programming to uncover business insights and trend.

Learn how to leverage on the power of Python Programming to deploy sophisticated statistical algorithms and models to advance Data Science, Artificial Intelligence / Machine Learning capabilities in any industry verticals.


No pre-requisite. Advanced Data Science Professional is suitable for everyone.


Participants are required to attempt an examination upon completion of course. This exam tests a candidate’s knowledge and skills related to Data Science and Python Programming based on the syllabus covered

Participants are expected to score a minimum of 70% to pass the examination

Course Outline

Module 1
Introduction to Data Science

Data Science is a discipline on data, its application, and how it can be utilized to help companies and professionals to make better decisions. In this module, participants will be introduced to the core components of data science. Participants will also learn about how to craft a data science strategy that is both efficient and reliable.

Topics Covered

  • What is Data Science
  • Data Science Vs. Analytics
  • What is Data warehouse
  • Online Analytical Processing (OLAP)
  • MIS Reporting
  • Data Science and its Industry Relevance
  • Problems and Objectives in Different Industries
  • How to Harness the power of Data Science?
  • ELT vs ETL

Module 2
Deep Dive into Python Programming

Python Programming language is one of the most accessible and flexible programming languages available. The syntax is simplified and can be easily written. With its extensive libraries, it is no wonder that data professionals are using Python as their preferred language. In this module, participants will learn the fundamentals of Python Programming and some of its popular libraries for Data Science

Topics Covered

  • Python Editors & IDE
  • Custom Environment Settings
  • Basic Rules in Python
  • Most Common Packages / Libraries in Python (NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc)
  • Tuples, Lists, Dictionaries)
  • List and Dictionary Comprehensions
  • Variable & Value Labels –  Date & Time Values
  • Basic Operations - Mathematical - string - date
  • Reading and writing data
  • Simple plotting/Control flow/Debugging/Code profiling

Module 3
Importing / Exporting Data with Python

Reading / writing data one of the first steps to kickstarting any Data Science project. Participants will have the chance to experience first-hand how to read / write data from various sources

Topics Covered

  • Importing Data into from Various sources
  • Database Input (Connecting to database)
  • Viewing Data objects - sub setting, methods
  • Exporting Data to various formats

Module 4
Data Cleansing with Python

The accuracy and quality of any analysis depend on how well the data is being cleaned. Data cleaning can be used to detect and correct errors or anomalies in the data. In this module, participants will learn the art of data cleaning to enhance the quality of data.

Topics Covered

  • Cleaning of Data with Python
  • Steps to Data Manipulation
  • Python Tools for Data manipulation
  • User Defined Functions in Python
  • Stripping out extraneous information
  • Normalization of Data and Data Formatting
  • Important Python Packages e.g.Pandas, Numpy etc)

Module 5
Data Visualization with Python

Data visualization helps people see, interact, and understand data better. The right visualization can help align the understanding of various stakeholders. Participants will have the opportunity to learn how to use Python Programming to perform Data Visualization.

Topics Covered

  • Exploratory Data Analysis
  • Descriptive Statistics, Frequency Tables and Summarization
  • Univariate Analysis (Distribution of data & Graphical Analysis)
  • Bivariate Analysis(Cross Tabs, Distributions & Relationships, Graphical Analysis)
  • Creating Graphs
  • Important Packages for Exploratory Analysis(NumPy Arrays, Matplotlib, Pandas and scipy.stats etc)

Module 6
Statistics Fundamentals

Statistics are being used by Data Scientists to gather, review, analyze, and draw conclusions from data. Statistics are the core of machine learning algorithms, capturing, and translating data patterns into actionable evidence.

Topics Covered

  • Basic Statistics - Measures of Central Tendencies and Variance
  • Building blocks (Probability Distributions, Normal distribution, Central Limit Theorem)
  • Inferential Statistics (Sampling, Concept of Hypothesis Testing)
  • Statistical Methods: Z/t-tests (One sample, independent, paired), ANOVA, Correlation and Chi-square
  • Statistical Methods: ANOVA
  • Statistical Methods: Correlation and Chi-square

Module 7
Introduction to Machine Learning

Machine learning is a field of study that gives computers the ability to learn without being programmed extensively. It applies algorithms to process the data and get trained for delivering future predictions. In this module, participants will be introduced to the key concepts of Machine Learning and how it can be easily applied using Python Programming.

Topics Covered

  • Statistical Learning vs Machine Learning
  • Iteration and Evaluation
  • Supervised Learning vs Unsupervised Learning
  • Predictive Modelling - Data Pre-processing, Sampling, Model Building, Validation
  • Concept of Overfitting and Under fitting (Bias-Variance Trade off) & Performance Metrics
  • Cross ValidationTrain & Test, Bootstrapping, K-Fold validation etc

Module 8
Understanding Predictive Analytics

A statistical technique derived from data mining, machine learning, and predictive modeling by using data from past events to predict the future. Participants will experience first-hand how predictive analytics can be deployed using Python Programming.

Topics Covered

  • Introduction to Predictive Modelling
  • Types of Business Problems
  • Mapping of Techniques
  • Linear Regression
  • Logistic Regression
  • Segmentation - Cluster Analysis (K-Means / DBSCAN)
  • Decision Trees (CHAID/CART/CD 5.0)
  • Time Series Forecasting

Module 9
Understanding A/B Testing Concepts

A/B testing is a framework that lets you set up your experiment to compare the performance of two versions of the same thing. It helps teams validate key questions, establishes causality, and helps data-driven teams looking to optimize their products.

Topics Covered

Topics Covered

  • Introduction to A/B Testing
  • Measuring Conversion for A/B Testing/li>
  • T-Test and P-Value
  • Measuring T-Statistics and P-Values using Python
  • A/B Test Gotchas
  • Novelty Effects, Seasonal Effects, and Selection of Bias
  • Data Pollution

Advanced Data Science Professional (ADSP) involves rigorous usage of real-time case studies, hands-on exercises and group discussions


Some Reasons Why Learners Choose CASUGOL

  • International Certification Body

  • Presence in 38 Countries

  • Developed by Industry Experts

  • More than 42,000 professionals passed through our education system

  • Flexible program design for all individuals

  • Learn from internationally renowned leading industry experts, academics, and researchers

  • Support for participants during and after training

  • Enhance competency of workforce and improve individual career prospect

  • Customization of programs for specific industry, organization, government agencies, statutory boards

  • Learn in a highly interactive, supportive and encouraging environment

  • Regular invitation to attend courses / workshops / seminars / events at complimentary rate

How to Register

Individual or Self-Sponsored Learners

  • STEP ONE: Select your preferred batch / category above

  • STEP TWO: Click on Add to Cart

  • STEP THREE: In the pop-up page, click on View Cart

  • STEP FOUR: In the Cart page, click on Proceed to Checkout

  • STEP FIVE: In the Checkout page, complete the Billing Details and click on Place Order

For corporate-sponsored participants, batch registration, or any questions on the course
Chat with an Education Officer

Certificate Verification

Certificate Verification

All certificates issued by CASUGOL are to individuals who have successfully completed CASUGOL Certification Programs / Executive Workshops and have fulfilled all requirements by demonstrating proficiency in applying the knowledge and skills acquired.

Click below to verify certificate